A Monte Carlo method for in silico modeling and visualization of Waddington's epigenetic landscape with intermediate details
2020-12
发表期刊BIOSYSTEMS (IF:2.0[JCR-2023],1.8[5-Year])
ISSN0303-2647
EISSN1872-8324
卷号198页码:#VALUE!
DOI10.1016/j.biosystems.2020.104275
摘要Waddington's epigenetic landscape is a classic metaphor for describing the cellular dynamics during the development modulated by gene regulation. Quantifying Waddington's epigenetic landscape by mathematical modeling would be useful for understanding the mechanisms of cell fate determination. A few computational methods have been proposed for quantitative modeling of landscape; however, to model and visualize the landscape of a high dimensional gene regulatory system with realistic details is still challenging. Here, we propose a Monte Carlo method for modeling the Waddington's epigenetic landscape of a gene regulatory network (GRN). The method estimates the probability distribution of cellular states by collecting a large number of time-course simulations with random initial conditions. By projecting all the trajectories into a 2-dimensional plane of dimensions i and j, we can approximately calculate the quasi-potential U(x(i), x(j), *) = -ln P(x(i,) x(j), *), where P(x(i), x(j), *) is the estimated probability of an equilibrium steady state or a non-equilibrium state. Compared to the state-of-the-art methods, our Monte Carlo method can quantify the global potential landscape (or emergence behavior) of GRN for a high dimensional system. The potential landscapes show that not only attractors represent stability, but the paths between attractors are also part of the stability or robustness of biological systems. We demonstrate the novelty and reliability of our method by plotting the potential landscapes of a few published models of GRN.
关键词Waddington's epigenetic landscape Monte Carlo Gene regulatory network Dynamical systems
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收录类别SCI ; SCIE
语种英语
WOS研究方向Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology
WOS类目Biology ; Mathematical & Computational Biology
WOS记录号WOS:000595260100012
出版者ELSEVIER SCI LTD
WOS关键词STOCHASTIC SIMULATION ; POTENTIAL LANDSCAPE ; PLURIPOTENT ; FRAMEWORK ; DYNAMICS
原始文献类型Article
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文献类型期刊论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/125965
专题信息科学与技术学院_硕士生
信息科学与技术学院_PI研究组_郑杰组
通讯作者Zheng, Jie
作者单位
1.Nanyang Technol Univ, Sch Comp Sci & Engn, Biomed Informat Lab, Singapore 639798, Singapore;
2.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China
通讯作者单位信息科学与技术学院
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Zhang, Xiaomeng,Chong, Ket Hing,Zhu, Lin,et al. A Monte Carlo method for in silico modeling and visualization of Waddington's epigenetic landscape with intermediate details[J]. BIOSYSTEMS,2020,198:#VALUE!.
APA Zhang, Xiaomeng,Chong, Ket Hing,Zhu, Lin,&Zheng, Jie.(2020).A Monte Carlo method for in silico modeling and visualization of Waddington's epigenetic landscape with intermediate details.BIOSYSTEMS,198,#VALUE!.
MLA Zhang, Xiaomeng,et al."A Monte Carlo method for in silico modeling and visualization of Waddington's epigenetic landscape with intermediate details".BIOSYSTEMS 198(2020):#VALUE!.
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